Publication in BibTeX Format

@ARTICLE{AICPub836:1981,
AUTHOR={Fischler, Martin A. and Bolles, Robert C.},
TITLE={Random Sample Consensus: A Paradigm for Model Fitting with Applications
to Image Analysis and Automated Cartography},
JOURNAL={Communications of the ACM},
PAGES={381-395},
NUMBER={6},
VOLUME={24},
YEAR={1981},
ABSTRACT={A new paradigm, Random Sample Consensus (RANSAC), for fitting a model
to experimental data is introduced. RANSAC is capable of interpreting/smoothing
data containing a significant percentage of gross errors, and is thus ideally
suited for applications in automated image analysis where interpretation is
based on the data provided by error-prone feature detectors. A major portion
of this paper describes the application of RANSAC to the Location Determination
Problem (LDP): Given an image depicting a set of landmarks with know locations,
determine that point in space from which the image was obtained. In response
to a RANSAC requirement, new results are derived on the minimum number of landmarks
needed to obtain a solution, and algorithms are presented for computing these
minimum-landmark solutions in closed form. These results provide the basis
for an automatic system that can solve the LDP under difficult viewing.}
}